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Record W4378976309 · doi:10.4018/ijesgt.304822

Evaluating the Sustainability Impacts of Green Roofs on Buildings

2023· article· en· W4378976309 on OpenAlexaff
Ali Zahabkar, Abobakr Al-Sakkaf, Ashutosh Bagchi

Bibliographic record

VenueInternational Journal of Environmental Sustainability and Green Technologies · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Heat Island Mitigation
Canadian institutionsConcordia University
Fundersnot available
KeywordsGreen roofSustainabilityRoofArchitectural engineeringCivil engineeringSustainable designEnvironmental scienceEnvironmental resource managementEngineeringEcology

Abstract

fetched live from OpenAlex

Widespread vegetated roofs, called green roofs, are becoming a popular option for sustainable design. Green roofs are capable of improving a variety of environmental parameters in urban areas. The construction of green roofs requires the consideration of many factors and parameters. For example, the structure of the building should be capable of carrying the extra weight of soil, water, and vegetation on the roof. The main objective of this paper is to study the impact of green roofs on buildings and to identify existing trends, technologies, and techniques. This paper investigates the implication of existing green roof technologies on structural design, energy demand, and life cycle cost. Using WUFI®, energy simulations were performed for the case study and the developed model was validated through cost analysis. Results showed that regional variations were sufficiently addressed through multi-level weight consideration in the proposed model. Findings from this study will be beneficial to urban planners and architects for the design and construction of more sustainable buildings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.303
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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